Identifying and Minimizing Measurement Invariance among Intersectional Groups
Rachel A. Gordon, Tianxiu Wang, Hai Nguyen, Ariel M. Aloe
This Element demonstrates how and why the alignment method can advance measurement fairness in developmental science. It explains its application to multi-category items in an accessible way, offering sample code and demonstrating an R package that facilitates interpretation of such items' multiple thresholds. It features the implications for group mean differences when differences in the thresholds between categories are ignored because items are treated as continuous, using an example of intersectional groups defined by assigned sex and race/ethnicity. It demonstrates the interpretation of item-level partial non-invariance results and their implications for group-level differences and encourages substantive theorizing regarding measurement fairness.
Năm:
2023
Nhà xuát bản:
Cambridge University Press
Ngôn ngữ:
english
Trang:
76
ISBN 10:
1009357743
ISBN 13:
9781009357746
File:
PDF, 4.37 MB
IPFS:
,
english, 2023